Power System Stabilizer Design Research Articles

Gradient based hybrid metaheuristics for robust tuning of power system stabilizers

Power System Stabilizers are controllers installed on synchronous generators to damp power system oscillations through the excitation control. These controllers can have either a conventional fixed structure composed by stages of gain and phase compensation or a flexible modern structure composed by three bands that correspond to a specific frequency range (low, intermediate and high frequency) in which each band is composed by two branches that are based on differential filters (with a gain, lead-lag blocks and a hybrid block). Power system stabilizers design is a hard and time consuming task and an alternative for tuning controllers is by using optimization methods. This paper presents three hybrid metaheuristics for the robust and coordinated design of power system stabilizers. The tuning procedure is modeled as an optimization problem which aims at maximizing the damping ratio coefficients in closed-loop operation. Robustness requirement is met by using multiple operating scenarios in the design stage. For solving the optimization problem, three metaheuristics (Gravitational Search Algorithm, Bat Algorithm and Particle Swarm Optimization) are combined with the Steepest Descent Method for local search capability enhancement. The proposed hybrid algorithms are applied to benchmark systems for validation.

Robust pole placement for power systems using two‐dimensional membership fuzzy constrained controllers

This study presents a design method of power system stabilisers (PSSs) to damp system oscillations. The design is based on fuzzy logic and linear matrix inequality (LMI) techniques. The design guarantees a robust pole placement in a desired region in the complex plane for different loading conditions. Due to system non-linearity and load dependency, the whole wide range of operating condition is divided into three subregions. For each subregion, a norm-bounded uncertainty linear model is developed and a robust LMI-based pole placer is designed considering controller constraint. Takagi–Sugeno fuzzy model is used to guarantee smoothly switching between the LMI-based controllers of the three subregions. The proposed technique avoids solving many LMIs as in the polytypic approach and avoids the infeasibility problem that might arise from solving the LMIs for the complete region of operation. In addition, the proposed fuzzy logic switching controller has reduced drastically the fuzzy rules due to the use of two-dimensional (2D) membership functions. Particle swarm optimisation is used to tune the proposed 2D membership functions to guarantee smooth switching of the controllers while maintaining the desired constraints. The simulation results of both single-machine and multi-machine power systems confirm the effectiveness of the proposed PSS design.

Robust design of multimachine power system stabilizers based on improved non-dominated sorting genetic algorithms

Power system stabilizers (PSSs) associated with generators are mandatory requirements for damping low-frequency oscillations of a multimachine power system. Nevertheless, PSSs work well at particular network configuration and steady-state conditions for which they were designed. Therefore, the aim of this paper is the design of a robust PSS able to ensure the stability of the system for a wide range of loading conditions and various faults with higher performance. The main motivation for this design is to simultaneously shift as much as could be possible the lightly damped and undamped system electromechanical modes, at different loading conditions and system configurations, into pre-specified zone in the s-plane called D-shape sector. Hence, the problem of robustly tuning the PSSs parameters is formulated as a multiobjective optimization problem (MOP) with an eigenvalue-based objective functions. An improved version of non-dominated sorting genetic algorithms (NSGAII) is proposed to solve this MOP. The performance of the proposed NSGAII-based PSS (NSGAII-PSS) under different loading conditions, system configurations and disturbances is tested and examined for different multimachine power systems. Eigenvalue analysis and nonlinear simulations show the effectiveness and robustness of the proposed controllers NSGAII-PSSs and their ability to provide efficient damping of low-frequency oscillations.

Neuro-fuzzy and nondominated sorting genetic algorithm based power system stabilizer design

Neuro-fuzzy and nondominated sorting genetic algorithm based power system stabilizer design

Coordinated Design of Under-Excitation Limiters and Power System Stabilizers

In this paper the authors tried to design a under excitation limiter and a power system stabilizer which can operate without any kind of interaction. The under excitation limiter (UEL) is intended to prevent reduction of generator excitation to a level where the steady state stability limit or the stator core end-region heating limit is exceeded. The power system stabilizer (PSS) uses auxiliary stabilizing signals to control the excitation system so as to improve power system dynamic performance.

Design and performance analysis of robust conventional power system stabiliser using cuckoo search algorithm

This article presents robust design of conventional power system stabiliser (CPSS) by using metaheuristic cuckoo search algorithm (CSA). The free coefficients of the CPSS are optimised using CSA connected with a single-machine infinite-bus (SMIB) power system at nominal operating condition. The performance of such optimised controller (CSA-CPSS) is compared with the performance of well established H∞-based power system stabiliser (H∞-PSS) over a wide range of operating conditions of the SMIB power system. The superiority of the proposed CSA-CPSS is validated with least value of settling time and the performance indices as ITAE, IAE and ISE of speed response over the H∞-PSS. Moreover, the superiority is proved by eigenvalue plot for considered 209 plants as a fan-shaped structure in left side of s-plane with damping factor as more than 0.1. The performance of CSA-CPSS is also considered for the multimachine power system. The CSA-CPSS outperforms the CDCARLA-CPSS, BFOA-CPSS and SPEA-CPSS in terms of reduced settling time, overshoot and performance indices.

Design and performance analysis of robust conventional power system stabiliser using cuckoo search algorithm

This article presents robust design of conventional power system stabiliser (CPSS) by using metaheuristic cuckoo search algorithm (CSA). The free coefficients of the CPSS are optimised using CSA connected with a single-machine infinite-bus (SMIB) power system at nominal operating condition. The performance of such optimised controller (CSA-CPSS) is compared with the performance of well established H∞-based power system stabiliser (H∞-PSS) over a wide range of operating conditions of the SMIB power system. The superiority of the proposed CSA-CPSS is validated with least value of settling time and the performance indices as ITAE, IAE and ISE of speed response over the H∞-PSS. Moreover, the superiority is proved by eigenvalue plot for considered 209 plants as a fan-shaped structure in left side of s-plane with damping factor as more than 0.1. The performance of CSA-CPSS is also considered for the multimachine power system. The CSA-CPSS outperforms the CDCARLA-CPSS, BFOA-CPSS and SPEA-CPSS in terms of reduced settling time, overshoot and performance indices.

A Memetic Algorithm for Power System Damping Controllers Design

This paper presents a hybrid algorithm for robust and coordinated design of power system stabilisers. Power system stabilisers are controllers installed on synchronous generators for excitation control in order to damp power system oscillations. The tuning procedure (gain and phase compensation stage) is cast as an optimisation problem which aims at maximising the damping coefficients in closed-loop operation. Robustness is dealt with by using multiple operating scenarios. For the optimisation problem solution, the bio-inspired Bat Algorithm is combined with the steepest descent method for local search capability enhancement. The proposed algorithm is applied to benchmark systems for validation.

Design of power system stabilizer for damping power system oscillations

Design of power system stabilizer for damping power system oscillations

Battery Energy Storage System-Based Stabilizers for Power System Oscillations Damping

To ensure secure and reliable operations of power systems, rapid damping of power system oscillations is unavoidable. This paper addresses the improved damping characteristics of a power system by integrating the Energy Storage System (ESS) such as a battery into a Flexible AC Transmission System (FACTS) device named the Battery Energy Storage System (BESS). Design of the BESS-based stabilizers is created to enhance the power system dynamic stability and damping profile. A modified Philips-Heffron model of a Single Machine Infinite Bus bar (SMIB) power system with BESS is established and analyzed. Improved damping characteristics of the power system oscillations are selected as performance criteria for the proposed design. Simulation results show the superior performance of the proposed design as compared to the coordinated design of BESS and conventional Power System Stabilizers (PSS). All the simulations are carried out in MATLAB/SIMULINK.

An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system

This paper deals with the backtracking search algorithm (BSA) optimization technique to solve the design problems of multi-machine power system stabilizers (PSSs) in large power system. Power system stability problem is formulated by an optimization problem using the LTI state space model of the power system. To conduct a comprehensive analysis, two test systems (2-AREA and 5-AREA) are considered to explain the variation of design performance with increase in system size. Additionally, two metaheuristic algorithms, namely bacterial foraging optimization algorithm (BFOA) and particle swarm optimization (PSO) are accounted to evaluate the overall design assessment. The obtained results show that BSA is superior to find consistent solution than BFOA and PSO regardless of system size. The damping performance that achieved from both test systems are sufficient to achieve fast system stability. System stability in linearized model is ensured in terms of eigenvalue shifting towards stability regions. On the other hand, damping performance in the non-linear model is evaluated in terms of overshoot and setting times. The obtained damping in both test systems are stable for BSA based design. However, BFOA and PSO based design perform worst in case of large power system. It is also found that the performance of BSA is not affected for large numbers of parameter optimization compared to PSO, and BFOA optimization techniques. This unique feature encourages recommending the developed backtracking search algorithm for PSS design of large multi-machine power system.

Interarea Power System Oscillations Damping via AI-based Referential Integrity Variable-Structure Control

Abstract The design of power system stabilizer (PSS) is load-dependent and needs continuous adjustment at each operating condition. This paper aims at introducing a robust non-fragile PSS for interconnected power systems. The proposed controller has the capability of adaptively tuning online its rule-base through a variable-structure direct adaptive control algorithm in order to rigorously attain the desired objectives. The PSS controller acts on damping the electromechanical modes of oscillations not only through a wide range of operating conditions but also in presence of different disturbances. Using MATLABTM-Simulink, simulation results significantly verify that the proposed controller provides favorable performance and efficiently contributes towards enhancing the system dynamic behavior when applied to the four machines two-area power system that mimics the typical system behavior in actual operation. The interaction between the variable-structure adaptive fuzzy-based power system stabilizer (VS-AFPSS) and the existed typical ones inside the interconnected power systems has been explicitly discussed. Compared to other conventional controllers, VS-AFPSS enables better damping characteristics to both local and inter-area oscillation modes considering different operating conditions and sever disturbances.

Wind Energy Power System Stabilizer Design using H∞ Robust Technique based on Enhance ABC Optimal Power System

system stabilizers (PSS) are now regularly used in the industry to damp out power system oscillations. High performance excitation system have become very important as limited generation capacity and consumer desires for power continue to increase. In this work, enhanced Artificial Bee Colony (ABC) technique is applied to design a robust power system stabilizer (PSS) in order to improve transient and dynamic stabilities of a turbo-alternator connected to an infinite bus system. The design problem of the proposed controller is formulated as an optimization problem and enhanced ABC is employed to search for optimal controller parameters. The robust power system stabilizer (RPSS) is designed using enhanced ABC for designing the controllers for dynamical systems in electrical engineering. Comparisons are also made between the Conventional power system stabilizer with a strong action (CPSS) and PSS with H∞ optimization. The simulation results show the effectiveness of proposed method for a stabilizer by enhancing the performance and robustness.

Chaos suppression for a four-dimensional fundamental power system model using adaptive feedback control

In this paper, the problem of chaos suppression for a four-dimensional fundamental power system (FDFPS) model is considered via the design of a novel adaptive feedback controller. The period doubling bifurcation route to chaos and some dynamical behaviors of the power system are investigated in detail. Based on stability analysis using an energy-type Lyapunov function, a single adaptive feedback controller is derived to suppress chaotic oscillation in four-dimensional fundamental power systems. The proposed controller simplifies the design of power system stabilizer and provides an easy way to implement in practical power system control. In addition, effectiveness of damping out chaotic oscillation and robustness against parameter uncertainty and external disturbance also make the proposed control scheme applicable for industrial application. Simulation results illustrate the effectiveness, the robustness and the superiority of proposed control method.

Stable Tending Control of Complex Power Systems: An Example of Localized Design of Power System Stabilizers

Stable Tending Control of Complex Power Systems: An Example of Localized Design of Power System Stabilizers

Stable Tending Control of Complex Power Systems: An Example of Localized Design of Power System Stabilizers

Stable Tending Control of Complex Power Systems: An Example of Localized Design of Power System Stabilizers

Power System Stabilizer Design for Multi-machine Power System Using Genetic Algorithm

This paper uses genetic algorithm (GA) framework integrated with the classical Lyapunov’s parameter optimization method employing an Integral of Squared Error (ISE) criterion to optimally tune the parameters of the power system stabilizers (PSSs) for a multi-machine system, consisting of three machines and ten interconnected buses, which is taken from the national electric power grid of Ethiopia. The issue of optimally tuning the parameters of the PSS is converted into an optimization problem that is solved via the GA algorithm. Within the GA process, a potential solution – the PSS parameter setting – is coded as an individual, which is part of a population of such potential solutions randomly generated, and by applying the survival of the fitness principle based on each individual’s fitness with respect to the objective, a sound basis for finding the best individual, i.e. global optimum solution, is created. Simulation results are presented to show the effectiveness of the proposed approach, for various system loading conditions and other disturbances such as perturbation in mechanical torque inputs to the machines, and have been performed with satisfactory results with the design and integration of PSS to the power system investigated in this paper.

Optimal coordinated design of UPFC and PSS for improving power system performance by using multi-objective water cycle algorithm

This paper presents an optimal design for simultaneously locating unified power flow controller (UPFC) and power system stabilizer (PSS). The parameters of their controllers are also tuned coordinately to enhance the power system stability. A mixed integer nonlinear problem is obtained for the design procedure due to the characteristics of selected objective functions. A new population-based meta-heuristic algorithm, called water cycle algorithm (WCA) is used to solve this problem. The best Pareto optimal set is also attained by defining this problem as a multi-objective function. The simulations results on IEEE 39-bus power system confirm the efficiency and the superior performance of the proposed method when compared with other algorithms.

Design of Power System Stabilizer (PSS) to Enhance Power System Stability in Power System

Design of Power System Stabilizer (PSS) to Enhance Power System Stability in Power System

Power system stabilizer design based on optimal model reference adaptive system

Abstract This paper addresses an optimal model reference adaptive system (MRAS) to design power system stabilizer (PSS) in multi-machine electric power systems. Weighting factors of the proposed MRAS are adjusted by particle swarm optimization (PSO) as well as its input signal is limited by a normalization technique to assure network stability. The proposed modified-optimal MRAS-PSS is evaluated against conventional PSS to demonstrate its advantages. In order to investigate the performance of the proposed MRAS-PSS under parametric uncertainties, three operating conditions are defined and simulated. Several nonlinear and time-domain simulations are carried out to validate the viability and effectiveness of the proposed MRAS-PSS under network uncertainties.